icp-matrix-builder

ICP Matrix Builder

When to Use

• Launching outbound for a new company or product line
• Refining targeting after initial campaign data comes in
• Expanding into new verticals or market segments
• Building the foundation for any lead generation or ABM campaign

Framework

What an ICP Matrix Is (And Isn't)

An ICP Matrix is a structured scoring document that ranks and segments your ideal buyers across multiple dimensions. It's the bridge between "we sell to B2B companies" and "we target Series B SaaS companies with 100-500 employees who just hired their first VP of Sales."

It IS:

• A living document that evolves with campaign data
• A scoring framework that makes targeting decisions objective
• A segmentation tool that enables personalized outreach at scale

It is NOT:

• A one-time exercise you do during onboarding and forget
• A single persona description
• A firmographic filter (company size + industry alone is not an ICP)

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The 5 Dimensions of an ICP Matrix

Every complete ICP Matrix scores prospects across five dimensions:

Dimension 1: Firmographic Fit

Does the company match your ideal customer profile structurally?

Attribute	Tier 1 (Best)	Tier 2 (Good)	Tier 3 (Acceptable)	Disqualified
Company size	Define range	Define range	Define range	Too small/large
Revenue	Define range	Define range	Define range	Outside range
Industry	Primary verticals	Adjacent verticals	Emerging fit	No fit
Geography	Primary markets	Secondary markets	Expansion markets	Restricted
Business model	Exact match	Similar	Adaptable	Incompatible
Growth stage	Ideal stage	Adjacent stages	Possible fit	Wrong stage

How to fill this in:

1. Start with your best 10 customers — what do they have in common?
2. Look at your worst 10 customers — what disqualified them (in hindsight)?
3. The patterns that appear in your best but NOT your worst = your Tier 1 criteria

Dimension 2: Technographic Fit

Does their tech stack indicate they're a good fit?

Attribute	Signal Strength	Why It Matters
Uses your integration partners	Strong	Lower friction to adopt
Uses a competitor	Strong	Active buyer, proven budget
Tech stack complexity matches	Medium	Right sophistication level
Recently adopted adjacent tools	Medium	Active buying cycle
No relevant tech stack	Weak	May not understand the category

Dimension 3: Buying Intent Signals

Is this company likely to be in-market right now?

Signal	Intent Level	Scoring Weight
Hiring for the role your product serves	Very High	5x
Recent funding round	High	4x
Competitor evaluation (G2, review sites)	Very High	5x
Content consumption (webinars, guides)	Medium-High	3x
Website visits (if tracking available)	High	4x
Leadership change in relevant dept	Medium	2x
No detectable intent	Low	1x

Dimension 4: Persona Mapping

Who within the company should you target?

For each ICP tier, define 2-3 target personas:

Persona Attribute	What to Define
Title patterns	VP Sales, Director of Revenue, Head of Growth (include variants)
Department	Sales, Marketing, RevOps, Growth
Seniority level	C-Suite, VP, Director, Manager
Decision role	Economic buyer, Champion, Influencer, Blocker
Pain points	3-5 specific, measurable pains this persona faces
Buying triggers	What events push them to evaluate solutions
Success metrics	What KPIs they're measured on
Common objections	Top 3-5 reasons they say no

Dimension 5: Engagement Readiness

How likely is this company to respond to outbound?

Factor	High Readiness	Low Readiness
Previous interactions	Engaged before (event, content, trial)	Cold — no prior touchpoint
Outbound receptiveness	SMB/mid-market, growth-stage	Enterprise, heavily gatekept
Channel preference	Active on LinkedIn, responsive to email	Dark social, unreachable online
Sales cycle length	< 60 days	6+ months
Committee size	1-3 decision makers	5+ stakeholders

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The Tiering Framework

After scoring all five dimensions, segment accounts into tiers:

Tier	Criteria	Outreach Strategy	Volume
Tier 1: Bullseye	4-5 dimensions score "Strong"	Hyper-personalized, multi-channel, 8+ touches	5-10% of list
Tier 2: Strong Fit	3-4 dimensions score "Strong"	Signal-based personalization, email-first	20-30% of list
Tier 3: Good Fit	2-3 dimensions score "Strong"	Bucket personalization, email-only	40-50% of list
Tier 4: Stretch	1-2 dimensions score "Strong"	Test with small batch, generic angle	10-20% of list
Disqualified	0 dimensions score "Strong" OR has a DQ flag	Do not contact	Remove from list

Disqualification triggers (immediate removal regardless of other scores):

• Company too small to have budget
• Industry you can't serve
• Already a customer
• Competitor or partner (unless intentional)
• Bad data (no valid email, wrong person)

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Building the Matrix: 6-Step Process

Step 1: Analyze Your Best Customers

Pull your top 10-20 customers by: revenue, retention, NPS, speed-to-close, or expansion rate.

For each, document:

• Firmographics (size, revenue, industry, geo)
• What triggered them to buy
• Who the champion was (title, seniority)
• How long the sales cycle took
• What their tech stack looked like at purchase

Step 2: Analyze Your Worst Customers

Pull 10-20 churned or low-value customers. Document the same attributes.

The gap between best and worst = your ICP definition.

Step 3: Identify Scoring Patterns

Look for attributes that appear in 70%+ of your best customers but less than 30% of your worst:

Best Customers Pattern Analysis:
- 80% were Series A-B stage → Weight: High
- 75% had 50-200 employees → Weight: High
- 70% were hiring SDRs when they bought → Weight: Very High
- 60% were in B2B SaaS → Weight: Medium-High
- 50% had a VP Sales title as buyer → Weight: Medium

Step 4: Build the Scoring Model

Assign point values to each attribute:

Dimension	Attribute	Tier 1 Points	Tier 2 Points	Tier 3 Points
Firmographic	50-200 employees	10	5	2
Firmographic	B2B SaaS	8	4	2
Technographic	Uses Salesforce	6	3	1
Intent	Hiring SDRs	10	5	2
Intent	Recent funding	8	4	2
Persona	VP Sales title	6	3	1

Total possible: Sum of all Tier 1 points Tier thresholds: Tier 1 = 80%+, Tier 2 = 60-79%, Tier 3 = 40-59%, Below 40% = DQ

Step 5: Validate with Campaign Data

After running your first campaigns, compare:

• Positive reply rate by ICP tier
• Meeting rate by ICP tier
• Close rate by ICP tier

If Tier 2 accounts are outperforming Tier 1, your scoring model needs adjustment. The data will tell you which attributes actually predict buying behavior vs. which ones you assumed would.

Step 6: Iterate Quarterly

Every quarter, re-run the analysis:

• Which attributes correlated with closed deals?
• Which new signals appeared in your best customers?
• Has your product evolved to serve a different segment better?

Update the matrix. Adjust scoring weights. Re-tier your target accounts.

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Multiple ICP Segments

Most companies have 2-4 distinct ICP segments. Each needs its own matrix:

ICP Segment Map:
├── Segment A: "Growth-Stage SaaS" (Primary)
│   ├── Company: 50-500 employees, Series A-C, B2B SaaS
│   ├── Buyer: VP Sales / Head of Growth
│   └── Trigger: Hiring SDRs or scaling outbound
│
├── Segment B: "Agency Scaling" (Secondary)
│   ├── Company: 10-50 employees, digital agency, $2M-$10M revenue
│   ├── Buyer: Founder / CEO
│   └── Trigger: Hit referral ceiling, need predictable pipeline
│
└── Segment C: "Enterprise RevOps" (Emerging)
    ├── Company: 500-5000 employees, tech or professional services
    ├── Buyer: Director of RevOps / VP Sales Operations
    └── Trigger: Tech consolidation or efficiency mandate

Rule: Each segment gets its own campaigns, its own copy, and its own personalization strategy. Never blend segments in a single campaign.

Templates

ICP Matrix Template

# ICP Matrix: {{Company/Product Name}}
# Version: {{version}} | Last Updated: {{date}}

## Segment: {{segment_name}}

### Firmographic Profile
| Attribute | Tier 1 | Tier 2 | Tier 3 | DQ |
|-----------|--------|--------|--------|----|
| Company size | ___ | ___ | ___ | ___ |
| Revenue | ___ | ___ | ___ | ___ |
| Industry | ___ | ___ | ___ | ___ |
| Geography | ___ | ___ | ___ | ___ |
| Business model | ___ | ___ | ___ | ___ |
| Growth stage | ___ | ___ | ___ | ___ |

### Target Personas (Ranked by Priority)
| Rank | Title Pattern | Seniority | Decision Role | Key Pain |
|------|--------------|-----------|---------------|----------|
| P1 | ___ | ___ | ___ | ___ |
| P2 | ___ | ___ | ___ | ___ |
| P3 | ___ | ___ | ___ | ___ |

### Intent Signals (Ranked by Weight)
| Signal | Weight (1-5) | Detection Source |
|--------|-------------|-----------------|
| ___ | ___ | ___ |
| ___ | ___ | ___ |
| ___ | ___ | ___ |

### Scoring Thresholds
| Tier | Min Score | Outreach Strategy |
|------|-----------|-------------------|
| Tier 1 | ___ | ___ |
| Tier 2 | ___ | ___ |
| Tier 3 | ___ | ___ |
| DQ | Below ___ | Do not contact |

### Validation Metrics (Update Quarterly)
| Metric | Tier 1 | Tier 2 | Tier 3 |
|--------|--------|--------|--------|
| Positive reply rate | ___ | ___ | ___ |
| Meeting rate | ___ | ___ | ___ |
| Close rate | ___ | ___ | ___ |
| Avg deal size | ___ | ___ | ___ |

Tips

• Your ICP is not who you CAN sell to — it's who you SHOULD sell to. The narrower your ICP, the higher your conversion rates.
• Start with 1 segment, not 4. Validate one ICP completely before expanding to adjacent segments.
• The #1 mistake in ICP development: using only firmographic data. A 100-person SaaS company that just raised Series B and is hiring 5 SDRs is a completely different prospect than a 100-person SaaS company that's been flat for 3 years. Same firmographics, wildly different intent.
• Interview your sales team. They know which deals close fast and which are painful — that pattern recognition is your ICP definition.
• If you don't have 10 customers to analyze yet, start with competitor customer analysis. Who are THEIR best customers? That's your starting ICP.
• Update your matrix every time you close (or lose) a significant deal. What did you learn? Did it match your scoring model?

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Progressive disclosure: load industry-specific ICP templates and scoring benchmarks only when building a matrix for a specific vertical.